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<div class="title">covariance_sampling.h</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * Copyright (c) 2009-2012, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Copyright (c) 2012-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * are met:</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *  * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *    notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> *    disclaimer in the documentation and/or other materials provided</span></div>
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<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> *    from this software without specific prior written permission.</span></div>
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<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="comment"> * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN</span></div>
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<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="comment"> * POSSIBILITY OF SUCH DAMAGE.</span></div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> * $Id$</span></div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160; </div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#ifndef PCL_FILTERS_COVARIANCE_SAMPLING_H_</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#define PCL_FILTERS_COVARIANCE_SAMPLING_H_</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160; </div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#include &lt;pcl/filters/filter_indices.h&gt;</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160; </div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="keyword">namespace </span>pcl</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;{</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>NT&gt;</div>
<div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html">   62</a></span>&#160;  <span class="keyword">class </span><a class="code" href="classpcl_1_1_covariance_sampling.html">CovarianceSampling</a> : <span class="keyword">public</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices</a>&lt;PointT&gt;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  {</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;      <span class="keyword">using</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices&lt;PointT&gt;::filter_name_</a>;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;      <span class="keyword">using</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices&lt;PointT&gt;::getClassName</a>;</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      <span class="keyword">using</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices&lt;PointT&gt;::indices_</a>;</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;      <span class="keyword">using</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices&lt;PointT&gt;::input_</a>;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;      <span class="keyword">using</span> <a class="code" href="classpcl_1_1_filter_indices.html">FilterIndices&lt;PointT&gt;::initCompute</a>;</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160; </div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;      <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="classpcl_1_1_point_cloud.html">FilterIndices&lt;PointT&gt;::PointCloud</a> <a class="code" href="classpcl_1_1_point_cloud.html">Cloud</a>;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;      <span class="keyword">typedef</span> <span class="keyword">typename</span> Cloud::Ptr CloudPtr;</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;      <span class="keyword">typedef</span> <span class="keyword">typename</span> Cloud::ConstPtr CloudConstPtr;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;      <span class="keyword">typedef</span> <span class="keyword">typename</span> pcl::PointCloud&lt;PointNT&gt;::ConstPtr NormalsConstPtr;</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keyword">public</span>:</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;      <span class="keyword">typedef</span> boost::shared_ptr&lt; CovarianceSampling&lt;PointT, PointNT&gt; &gt; Ptr;</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;      <span class="keyword">typedef</span> boost::shared_ptr&lt; const CovarianceSampling&lt;PointT, PointNT&gt; &gt; ConstPtr;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#a5a3e08593454dc450d55638402bdf9a5">   80</a></span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a5a3e08593454dc450d55638402bdf9a5">CovarianceSampling</a> ()</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;      { <a class="code" href="classpcl_1_1_filter.html#ad700c7ab56dc82ad8811b87e9f793751">filter_name_</a> = <span class="stringliteral">&quot;CovarianceSampling&quot;</span>; }</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160; </div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#ac705c2a818792c53b1a3c64b6eca676d">   87</a></span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#ac705c2a818792c53b1a3c64b6eca676d">setNumberOfSamples</a> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> samples)</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;      { <a class="code" href="classpcl_1_1_covariance_sampling.html#ad5e2ddf8d42b6a47fbf16398eff29833">num_samples_</a> = samples; }</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#ada5284058f054b0e18dcfbbf3b876079">   92</a></span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#ada5284058f054b0e18dcfbbf3b876079">getNumberOfSamples</a> ()<span class="keyword"> const</span></div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;<span class="keyword">      </span>{ <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1_covariance_sampling.html#ad5e2ddf8d42b6a47fbf16398eff29833">num_samples_</a>); }</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;      <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00099"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#a77f474e133011e1cff3130c6c3732b78">   99</a></span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a77f474e133011e1cff3130c6c3732b78">setNormals</a> (<span class="keyword">const</span> NormalsConstPtr &amp;normals)</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;      { <a class="code" href="classpcl_1_1_covariance_sampling.html#a498a76c8589afc1a508f4daada7ab64d">input_normals_</a> = normals; }</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      <span class="keyword">inline</span> NormalsConstPtr</div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#aab9deb8cf8f2825c391ec6d87975ba5a">  104</a></span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#aab9deb8cf8f2825c391ec6d87975ba5a">getNormals</a> ()<span class="keyword"> const</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;<span class="keyword">      </span>{ <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1_covariance_sampling.html#a498a76c8589afc1a508f4daada7ab64d">input_normals_</a>); }</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160; </div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160; </div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160; </div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      <span class="keywordtype">double</span></div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a82eac9e85ffed525bb467e3cd58a87e4">computeConditionNumber</a> ();</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160; </div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;      <span class="keyword">static</span> <span class="keywordtype">double</span></div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a82eac9e85ffed525bb467e3cd58a87e4">computeConditionNumber</a> (<span class="keyword">const</span> Eigen::Matrix&lt;double, 6, 6&gt; &amp;covariance_matrix);</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160; </div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#ab2210a7ae6ce3f6bf71e13ee3cf9249b">computeCovarianceMatrix</a> (Eigen::Matrix&lt;double, 6, 6&gt; &amp;covariance_matrix);</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160; </div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <span class="keyword">protected</span>:</div>
<div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#ad5e2ddf8d42b6a47fbf16398eff29833">  135</a></span>&#160;      <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classpcl_1_1_covariance_sampling.html#ad5e2ddf8d42b6a47fbf16398eff29833">num_samples_</a>;</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160; </div>
<div class="line"><a name="l00138"></a><span class="lineno"><a class="line" href="classpcl_1_1_covariance_sampling.html#a498a76c8589afc1a508f4daada7ab64d">  138</a></span>&#160;      NormalsConstPtr <a class="code" href="classpcl_1_1_covariance_sampling.html#a498a76c8589afc1a508f4daada7ab64d">input_normals_</a>;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;      std::vector&lt;Eigen::Vector3f, Eigen::aligned_allocator&lt;Eigen::Vector3f&gt; &gt; scaled_points_;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160; </div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;      <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;      initCompute ();</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a7d073302aaf53592ebaad290041162c4">applyFilter</a> (<a class="code" href="classpcl_1_1_point_cloud.html">Cloud</a> &amp;output);</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;      <span class="keywordtype">void</span></div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      <a class="code" href="classpcl_1_1_covariance_sampling.html#a7d073302aaf53592ebaad290041162c4">applyFilter</a> (std::vector&lt;int&gt; &amp;indices);</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160; </div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      <span class="keyword">static</span> <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      sort_dot_list_function (std::pair&lt;int, double&gt; a,</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                              std::pair&lt;int, double&gt; b)</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;      { <span class="keywordflow">return</span> (a.second &gt; b.second); }</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160; </div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keyword">public</span>:</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      EIGEN_MAKE_ALIGNED_OPERATOR_NEW</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  };</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;}</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;<span class="preprocessor">#ifdef PCL_NO_PRECOMPILE</span></div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;<span class="preprocessor">#include &lt;pcl/filters/impl/covariance_sampling.hpp&gt;</span></div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160; </div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* PCL_FILTERS_COVARIANCE_SAMPLING_H_ */</span><span class="preprocessor"></span></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html">pcl::CovarianceSampling</a></div><div class="ttdoc">Point Cloud sampling based on the 6D covariances. It selects the points such that the resulting cloud...</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:63</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_a498a76c8589afc1a508f4daada7ab64d"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#a498a76c8589afc1a508f4daada7ab64d">pcl::CovarianceSampling::input_normals_</a></div><div class="ttdeci">NormalsConstPtr input_normals_</div><div class="ttdoc">The normals computed at each point in the input cloud</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:138</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_a5a3e08593454dc450d55638402bdf9a5"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#a5a3e08593454dc450d55638402bdf9a5">pcl::CovarianceSampling::CovarianceSampling</a></div><div class="ttdeci">CovarianceSampling()</div><div class="ttdoc">Empty constructor.</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:80</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_a77f474e133011e1cff3130c6c3732b78"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#a77f474e133011e1cff3130c6c3732b78">pcl::CovarianceSampling::setNormals</a></div><div class="ttdeci">void setNormals(const NormalsConstPtr &amp;normals)</div><div class="ttdoc">Set the normals computed on the input point cloud</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:99</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_a7d073302aaf53592ebaad290041162c4"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#a7d073302aaf53592ebaad290041162c4">pcl::CovarianceSampling::applyFilter</a></div><div class="ttdeci">void applyFilter(Cloud &amp;output)</div><div class="ttdoc">Sample of point indices into a separate PointCloud</div><div class="ttdef"><b>Definition:</b> covariance_sampling.hpp:259</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_a82eac9e85ffed525bb467e3cd58a87e4"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#a82eac9e85ffed525bb467e3cd58a87e4">pcl::CovarianceSampling::computeConditionNumber</a></div><div class="ttdeci">double computeConditionNumber()</div><div class="ttdoc">Compute the condition number of the input point cloud. The condition number is the ratio between the ...</div><div class="ttdef"><b>Definition:</b> covariance_sampling.hpp:85</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_aab9deb8cf8f2825c391ec6d87975ba5a"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#aab9deb8cf8f2825c391ec6d87975ba5a">pcl::CovarianceSampling::getNormals</a></div><div class="ttdeci">NormalsConstPtr getNormals() const</div><div class="ttdoc">Get the normals computed on the input point cloud</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:104</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_ab2210a7ae6ce3f6bf71e13ee3cf9249b"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#ab2210a7ae6ce3f6bf71e13ee3cf9249b">pcl::CovarianceSampling::computeCovarianceMatrix</a></div><div class="ttdeci">bool computeCovarianceMatrix(Eigen::Matrix&lt; double, 6, 6 &gt; &amp;covariance_matrix)</div><div class="ttdoc">Computes the covariance matrix of the input cloud.</div><div class="ttdef"><b>Definition:</b> covariance_sampling.hpp:137</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_ac705c2a818792c53b1a3c64b6eca676d"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#ac705c2a818792c53b1a3c64b6eca676d">pcl::CovarianceSampling::setNumberOfSamples</a></div><div class="ttdeci">void setNumberOfSamples(unsigned int samples)</div><div class="ttdoc">Set number of indices to be sampled.</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:87</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_ad5e2ddf8d42b6a47fbf16398eff29833"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#ad5e2ddf8d42b6a47fbf16398eff29833">pcl::CovarianceSampling::num_samples_</a></div><div class="ttdeci">unsigned int num_samples_</div><div class="ttdoc">Number of indices that will be returned.</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:135</div></div>
<div class="ttc" id="aclasspcl_1_1_covariance_sampling_html_ada5284058f054b0e18dcfbbf3b876079"><div class="ttname"><a href="classpcl_1_1_covariance_sampling.html#ada5284058f054b0e18dcfbbf3b876079">pcl::CovarianceSampling::getNumberOfSamples</a></div><div class="ttdeci">unsigned int getNumberOfSamples() const</div><div class="ttdoc">Get the value of the internal num_samples_ parameter.</div><div class="ttdef"><b>Definition:</b> covariance_sampling.h:92</div></div>
<div class="ttc" id="aclasspcl_1_1_filter_html_ad700c7ab56dc82ad8811b87e9f793751"><div class="ttname"><a href="classpcl_1_1_filter.html#ad700c7ab56dc82ad8811b87e9f793751">pcl::Filter::filter_name_</a></div><div class="ttdeci">std::string filter_name_</div><div class="ttdoc">The filter name.</div><div class="ttdef"><b>Definition:</b> filter.h:166</div></div>
<div class="ttc" id="aclasspcl_1_1_filter_indices_html"><div class="ttname"><a href="classpcl_1_1_filter_indices.html">pcl::FilterIndices</a></div><div class="ttdoc">FilterIndices represents the base class for filters that are about binary point removal....</div><div class="ttdef"><b>Definition:</b> filter_indices.h:76</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a></div><div class="ttdoc">PointCloud represents the base class in PCL for storing collections of 3D points.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:173</div></div>
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